The objective is to convene the Seventh International Workshop on Seizure Prediction (IWSP). This meeting focuses on the development of treatments for epilepsy especially based on closed loop seizure prediction, detection and interventions. The IWSP series is a unique forum that brings together an international interdisciplinary group involving epileptologists, engineers, physicists, mathematicians, neurosurgeons and neuroscientists. While this goal has not changed over the previous six workshops, the group has recognized that there needs to be a balance in developing an understanding of the biological mechanisms underlying epilepsy in parallel with treatment oriented approaches in order to improve the performance of seizure prediction, detection and control algorithms, and with the ultimate objective of improving quality of life for the epileptic patient. At a fundamental level, the goal of seizure prediction is to identify the underlying mechanisms of seizure generation and to engineer systems that will detect those dynamics and provide for intervention. Activity in the field of seizure prediction and control is reinvigorated.The clinical trial of the NeuroVista seizure advisory system produced months-to-years long ambulatory intra-cranial EEG from human subjects, and demonstrated that seizure prediction is feasible. The recent FDA approval of the Neuropace RNS closed loop seizure control device has further galvanized the field. These two thrusts provide realistic and relevant data streams to advance this field. This seventh meeting will address three key themes: (1) Seizure prediction from months-to-years long recordings; (2) Model-based data assimilation for time series analysis, neuro-intervention and feedback control; and (3) Multi-modal neuroimaging and computational modeling to assess the spatial origin of seizures and the epileptic network at multiple scales. These themes will be complemented by the prior topics in the IWSP series. In line with theme (1) there will be a human-data seizure prediction contest using recordings from the long-term NeuroVista Seizure Advisory System clinical trial. Recent access to ultra long-term high-quality data means there is now greater ability to evaluate both seizure prediction algorithms and computational modeling in ways that were previously constrained by the limited physiological measurements. Through the modeling themes we aim to build bridges between theoretical, computational, physiological and clinical metrics to arrive at new approaches to understand epileptic seizure mechanisms across all scales of the brain, and thereby develop improved methods for seizure prediction, detection and control. NIH funding is sought for travel support to encourage US participation.